Kyriakou, C. (Charalampia)

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    International Myeloma Working Group risk stratification model for smoldering multiple myeloma (SMM)
    (2020) Gonzalez-Calle, V. (Veronica); Durie, B. (B.); Hansson, M. (Markus); Ukropec, J. (Jon); Usmani, S.Z. (Saad Z.); Merlini, G. (G.); Zamagni, E. (Elena); Min, C.K. (Chang-Ki); Qi, M. (Ming); Ludwig, H. (Heinz); Hajek, R. (R.); Mateos, M.V. (María Victoria); De-Larrea, C.F. (Carlos Fernández); Esteves, G. (Graça); Kumar, S. (Shaji); Gozzetti, A. (A.); Morgan, G.J. (Gareth J.); Geraldes, C. (Catarina); Kyriakou, C. (Charalampia); Goldschmidt, H. (Hartmut); Kim, B.S. (Byung-Su); Dimopoulos, M.A. (Meletios A.); Kastritis, E. (Efstathios); Weiss, B.M. (Brendan M.); Fantl, D. (Dorotea); Rajkumar, S.V. (S. Vincent); San-Miguel, J.F. (Jesús F.); Leleu, X. (Xavier); Garderet, L. (Laurent)
    Smoldering multiple myeloma (SMM) is an asymptomatic precursor state of multiple myeloma (MM). Recently, MM was redefined to include biomarkers predicting a high risk of progression from SMM, thus necessitating a redefinition of SMM and its risk stratification. We assembled a large cohort of SMM patients meeting the revised IMWG criteria to develop a new risk stratification system. We included 1996 patients, and using stepwise selection and multivariable analysis, we identified three independent factors predicting progression risk at 2 years: serum M-protein >2 g/dL (HR: 2.1), involved to uninvolved free light-chain ratio >20 (HR: 2.7), and marrow plasma cell infiltration >20% (HR: 2.4). This translates into 3 categories with increasing 2-year progression risk: 6% for low risk (38%; no risk factors, HR: 1); 18% for intermediate risk (33%; 1 factor; HR: 3.0), and 44% for high risk (29%; 2–3 factors). Addition of cytogenetic abnormalities (t(4;14), t(14;16), +1q, and/or del13q) allowed separation into 4 groups (low risk with 0, low intermediate risk with 1, intermediate risk with 2, and high risk with ≥3 risk factors) with 6, 23, 46, and 63% risk of progression in 2 years, respectively. The 2/20/20 risk stratification model can be easily implemented to identify high-risk SMM for clinical research and routine practice and will be widely applicable.